Neuro-Symbolic Agentic Protocol

AI Knowledge Representation Language Specification

The AI Knowledge Representation Language Specification is to formally define a unified, declarative knowledge-representation framework built entirely on standard Python syntax, enabling Python code to function simultaneously as executable logic, a dependency-tracked data model, and a neuro-symbolic reasoning language. It establishes how variables, classes, objects, rules, and expressions are interpreted semantically—not as one-time imperative operations, but as persistent logical relationships that automatically maintain consistency as values change. The specification also defines how neural insights (e.g., patterns learned by LLMs) can be translated into explicit symbolic structures, how declarative updates propagate through an in-memory dependency graph, how constraints, queries, and class-level reasoning operate, and how persistence, transactions, and exception handling maintain system integrity. Overall, the specification provides the conceptual and operational foundation for a Python-based neuro-symbolic AI system in which computation, logic representation, and data persistence merge into a single coherent model.

AI Knowledge Representation Language Specification